Assistants grounded in your knowledge base, support and sales automation, content generation and personalization. Built on OpenAI, Anthropic and open-source LLMs — with answer quality under control.
AI integration means connecting language models to your website, CRM and internal data so they solve specific tasks: advise customers, qualify leads, answer questions from documentation, write and translate content.
The key difference from a “chat widget with ChatGPT” is working on your data. We build a knowledge base from your site, price lists, policies and past conversations, connect it to the model via RAG (retrieval-augmented generation), and set the tone and boundaries. The assistant answers like your best manager, doesn't make things up and hands complex cases to a human.
We roll out in stages: first one scenario with a measurable effect — say, answering common questions and capturing leads at night — then expand: CRM integration, personalization, automation of internal processes.
The same questions about delivery, payment and availability — the assistant answers instantly, any time.
An assistant over your docs and cases helps the customer understand the product and passes a warm lead to sales.
Booking, choosing a program or specialist, answering organizational questions without loading your front desk.
Drafts, SEO descriptions, translations and content recommendations tailored to the reader.
Problem
Requests at 11 pm wait until morning; by then half the customers have messaged a competitor.
Our fix
The assistant replies instantly, qualifies the request and logs the contact in your CRM with a note for the manager.
Problem
Support spends 80% of its time answering the same 20 questions.
Our fix
Knowledge base + RAG: routine questions get closed automatically, people handle the complex cases.
Problem
You tried an off-the-shelf chatbot — it hallucinated and went off topic.
Our fix
Answers strictly from your documents, with sources cited and a hand-off to a human when unsure. Tested on real conversations before launch.
Problem
Content for the site and product cards takes weeks.
Our fix
Generation and structuring of content with editorial review — many times faster, same quality bar.
09
We analyze inquiries, conversations and processes — and pick the tasks with the biggest impact.
We collect and structure data: site, documents, price lists, FAQ, conversation history.
Vector search over your data so answers are accurate and backed by sources.
Role, boundaries, communication style, “I don't know” handling, spam and prompt-injection protection.
A chat widget on the site, a Telegram / WhatsApp bot, a voice channel or an in-app assistant.
CRM (HubSpot, Pipedrive, Bitrix24), calendar, payments, product database, e-mail, internal APIs.
Escalation to a person with the full conversation context, messenger notifications.
Conversation dashboard, answer ratings, inquiry topics, conversion to leads.
Access control, PII masking, choice of model and hosting region.
Stack and tools
10
Total5–20 days
We review inquiries and processes, pick the first scenario and the success metrics.
We collect, clean and label the data. We agree on what the assistant can and cannot say.
A working assistant on staging. We run real conversations, refine prompts and data.
Site widget or bot, CRM, notifications, human hand-off, analytics.
Launch on real traffic, a week of quality monitoring, knowledge base updates.
from $500
5–7 days
A site or Telegram chatbot grounded in your knowledge base.
from $1,100
10–14 days
An assistant embedded into sales and support.
from $2,200
3–5 weeks
AI agents and end-to-end process automation.
Model API usage is billed separately, pay-as-you-go — typically $15–150/mo depending on load. We help pick the most cost-efficient model.
| Criteria | Vectra | SaaS chat widget | No AI |
|---|---|---|---|
| Answer quality | On your data, with sources | Generic answers, frequent errors | Depends on staff availability |
| Process integration | CRM, booking, payments, internal APIs | A limited set of connectors | Manual work |
| Control and data | Your data, your choice of model and region | Data sits with a third party | — |
| Cost | One-off build + API pay-as-you-go | Monthly fee per seat / conversation | Support payroll grows with load |
| Growth | Any scenario as you scale | Within the vendor's features | — |
A basic assistant on your data starts at $500; CRM and messenger integration from $1,100. Plus model API usage, pay-as-you-go: for a small business that's usually $15–150 a month. The exact estimate comes after the audit.
We ground answers in your documents (RAG), give the model strict boundaries and an “I don't know — handing over” path. Before launch we run dozens of real conversations and measure accuracy. That's the key difference from a chat with “bare” ChatGPT.
OpenAI, Anthropic Claude, plus open-source models (Llama, Qwen) on your own server. If data must stay in-house or in a specific region, we host the model privately or pick a compliant provider.
Through the official APIs of HubSpot, Pipedrive, Bitrix24 and others: we create a lead with the conversation transcript, qualification and source, assign a manager and send a notification to Telegram or Slack.
We mask personal data before it reaches the model, restrict access and log requests. We help describe the processing in your privacy policy in line with GDPR or local regulation.
Yes — and we recommend it. The first scenario, such as answering common questions and capturing leads, launches within a week. Then we expand based on real conversation statistics.
In most cases fine-tuning isn't necessary — a knowledge base with RAG is enough. It's cheaper, faster and lets you update data instantly. We fine-tune for a very specific style or narrow tasks.
Tell us about the task — we'll propose a scenario, a model and an estimate. Free consultation.
